This can be used, for example, to changeĬonfidence_level, change method, or see the effect of performingĪdditional resampling without repeating computations. To include the previous bootstrap distribution in the new bootstrapĭistribution. Provide the result object returned by a previous call to bootstrap bootstrap_result BootstrapResult, optional Interval ( 'basic'), or the bias-corrected and accelerated bootstrapĬonfidence interval ( 'BCa'). ( 'percentile'), the ‘basic’ (AKA ‘reverse’) bootstrap confidence Whether to return the ‘percentile’ bootstrap confidence interval The confidence level of the confidence interval. The axis of the samples in data along which the statistic isĬalculated. Whether the statistic treats corresponding elements of the samples Bootstrap, Bulma) is that its built with a modern theming approach (CSS variables). Use ofĪ vectorized statistic typically reduces computation time. The main difference between Infima and existing CSS frameworks (e.g. Will be set True if axis is a parameter of statistic. If True, statistic will be passed keywordĪrgument axis and is expected to calculate the statistic along axis Keyword argument axis and is expected to calculate the statistic If vectorized is set False, statistic will not be passed (or batch = max(n_resamples, n) for method='BCa'). Default is None, in which case batch = n_resamples Memory usage is O( batch`*``n`), where n is the The number of resamples to process in each vectorized call to The number of resamples performed to form the bootstrap distribution Vectorized to compute the statistic along the provided axis. Statistic must also accept a keyword argument axis and be ![]() Statistic must be a callable that accepts len(data) samplesĪs separate arguments and returns the resulting statistic. Statistic for which the confidence interval is to be calculated. Parameters : data sequence of array-likeĮach element of data is a sample from an underlying distribution. ![]() If the samples in data are taken at random from their respectiveĭistributions \(n\) times, the confidence interval returned byīootstrap will contain the true value of the statistic for thoseĭistributions approximately confidence_level \(\, \times \, n\) times. (‘reverse percentile’) and 'BCa' (‘bias-corrected and accelerated’) Two more common methods are available, 'basic' While the 'percentile' method is the most intuitive, it is rarely (with replacement) of the same size as the original sample.Ĭompute the bootstrap distribution of the statistic: for each set ofĭetermine the confidence interval: find the interval of the bootstrapĬontains confidence_level of the resampled statistic values. N_resamples, take a random sample of the original sample Resample the data: for each sample in data and for each of When method is 'percentile', a bootstrap confidence interval isĬomputed according to the following procedure. bootstrap ( data, statistic, *, n_resamples = 9999, batch = None, vectorized = None, paired = False, axis = 0, confidence_level = 0.95, method = 'BCa', bootstrap_result = None, random_state = None ) #Ĭompute a two-sided bootstrap confidence interval of a statistic. Statistical functions for masked arrays ( K-means clustering and vector quantization (
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